docs: def get_correlation(self, t1, t2):
          """
          Computes the correlation coefficient for the specified periods.
  
          :param float t1:
              First period of interest.
  
          :param float t2:
              Second period of interest.
  
          :return float rho:
              The predicted correlation coefficient.
          """
  
          t_min = min(t1, t2)
          t_max = max(t1, t2)
  
          c1 = 1.0
          c1 -= np.cos(np.pi / 2.0 - np.log(t_max / max(t_min, 0.109)) * 0.366)
  
          if t_max < 0.2:
              c2 = 0.105 * (1.0 - 1.0 / (1.0 + np.exp(100.0 * t_max - 5.0)))
              c2 = 1.0 - c2 * (t_max - t_min) / (t_max - 0.0099)
          else:
              c2 = 0
  
          if t_max < 0.109:
              c3 = c2
          else:
              c3 = c1
  
          c4 = c1
          c4 += 0.5 * (np.sqrt(c3) - c3) * (1.0 + np.cos(np.pi * t_min / 0.109))
  
          if t_max <= 0.109:
              rho = c2
          elif t_min > 0.109:
              rho = c1
          elif t_max < 0.2:
              rho = min(c2, c4)
          else:
              rho = c4
  
          return rho